Association of waist-to-hip ratio adjusted for body mass index with cognitive impairment in middle-aged and elderly patients with type 2 diabetes mellitus: a cross-sectional study.
Abdominal obesity
Cognitive impairment
Type 2 diabetes mellitus
Waist-to-hip ratio adjusted for body mass index
Journal
BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562
Informations de publication
Date de publication:
06 Sep 2024
06 Sep 2024
Historique:
received:
05
01
2024
accepted:
04
09
2024
medline:
7
9
2024
pubmed:
7
9
2024
entrez:
6
9
2024
Statut:
epublish
Résumé
Numerous reports indicate that both obesity and type 2 diabetes mellitus (T2DM) are factors associated with cognitive impairment (CI). The objective was to assess the relationship between abdominal obesity as measured by waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and CI in middle-aged and elderly patients with T2DM. A cross-sectional study was conducted, in which a total of 1154 patients with T2DM aged ≥ 40 years were included. WHRadjBMI was calculated based on anthropometric measurements and CI was assessed utilizing the Montreal Cognitive Assessment (MoCA). Participants were divided into CI group (n = 509) and normal cognition group (n = 645). Correlation analysis and binary logistic regression were used to explore the relationship between obesity-related indicators including WHRadjBMI, BMI as well as waist circumference (WC) and CI. Meanwhile, the predictive power of these indicators for CI was estimated by receiver operating characteristic (ROC) curves. WHRadjBMI was positively correlated with MoCA scores, independent of sex. The Area Under the Curve (AUC) for WHRadjBMI, BMI and WC were 0.639, 0.521 and 0.533 respectively, and WHRadjBMI had the highest predictive power for CI. Whether or not covariates were adjusted, one-SD increase in WHRadjBMI was significantly related to an increased risk of CI with an adjusted OR of 1.451 (95% CI: 1.261-1.671). After multivariate adjustment, the risk of CI increased with rising WHRadjBMI quartiles (Q4 vs. Q1 OR: 2.980, 95%CI: 2.032-4.371, P for trend < 0.001). Our study illustrated that higher WHRadjBMI is likely to be associated with an increased risk of CI among patients with T2DM. These findings support the detrimental effects of excess visceral fat accumulation on cognitive function in middle-aged and elderly T2DM patients.
Sections du résumé
BACKGROUND
BACKGROUND
Numerous reports indicate that both obesity and type 2 diabetes mellitus (T2DM) are factors associated with cognitive impairment (CI). The objective was to assess the relationship between abdominal obesity as measured by waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and CI in middle-aged and elderly patients with T2DM.
METHODS
METHODS
A cross-sectional study was conducted, in which a total of 1154 patients with T2DM aged ≥ 40 years were included. WHRadjBMI was calculated based on anthropometric measurements and CI was assessed utilizing the Montreal Cognitive Assessment (MoCA). Participants were divided into CI group (n = 509) and normal cognition group (n = 645). Correlation analysis and binary logistic regression were used to explore the relationship between obesity-related indicators including WHRadjBMI, BMI as well as waist circumference (WC) and CI. Meanwhile, the predictive power of these indicators for CI was estimated by receiver operating characteristic (ROC) curves.
RESULTS
RESULTS
WHRadjBMI was positively correlated with MoCA scores, independent of sex. The Area Under the Curve (AUC) for WHRadjBMI, BMI and WC were 0.639, 0.521 and 0.533 respectively, and WHRadjBMI had the highest predictive power for CI. Whether or not covariates were adjusted, one-SD increase in WHRadjBMI was significantly related to an increased risk of CI with an adjusted OR of 1.451 (95% CI: 1.261-1.671). After multivariate adjustment, the risk of CI increased with rising WHRadjBMI quartiles (Q4 vs. Q1 OR: 2.980, 95%CI: 2.032-4.371, P for trend < 0.001).
CONCLUSIONS
CONCLUSIONS
Our study illustrated that higher WHRadjBMI is likely to be associated with an increased risk of CI among patients with T2DM. These findings support the detrimental effects of excess visceral fat accumulation on cognitive function in middle-aged and elderly T2DM patients.
Identifiants
pubmed: 39243030
doi: 10.1186/s12889-024-19985-7
pii: 10.1186/s12889-024-19985-7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2424Informations de copyright
© 2024. The Author(s).
Références
GBDDF Collaborators. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019. Lancet Public Health. 2022;7(2):e105–25.
doi: 10.1016/S2468-2667(21)00249-8
Klein S, Gastaldelli A, Yki-Jarvinen H, Scherer PE. Why does obesity cause diabetes? Cell Metab. 2022;34(1):11–20.
pubmed: 34986330
pmcid: 8740746
doi: 10.1016/j.cmet.2021.12.012
Stumvoll M, Goldstein BJ, van Haeften TW. Type 2 diabetes: principles of pathogenesis and therapy. Lancet. 2005;365(9467):1333–46.
pubmed: 15823385
doi: 10.1016/S0140-6736(05)61032-X
Biessels GJ, Deary IJ, Ryan CM. Cognition and diabetes: a lifespan perspective. Lancet Neurol. 2008;7(2):184–90.
pubmed: 18207116
doi: 10.1016/S1474-4422(08)70021-8
Arvanitakis Z, Wilson RS, Bienias JL, Evans DA, Bennett DA. Diabetes mellitus and risk of Alzheimer disease and decline in cognitive function. Arch Neurol. 2004;61(5):661–6.
pubmed: 15148141
doi: 10.1001/archneur.61.5.661
Smith MA, Zhu X, Tabaton M, Liu G, McKeel DW Jr, Cohen ML, et al. Increased iron and free radical generation in preclinical Alzheimer disease and mild cognitive impairment. J Alzheimers Dis. 2010;19(1):363–72.
pubmed: 20061651
pmcid: 2842004
doi: 10.3233/JAD-2010-1239
Li W, Sun L, Li G, Xiao S. Prevalence, Influence Factors and Cognitive Characteristics of Mild Cognitive Impairment in Type 2 Diabetes Mellitus. Front Aging Neurosci. 2019;11: 180.
pubmed: 31417393
pmcid: 6682644
doi: 10.3389/fnagi.2019.00180
Zhang Z, Zhang B, Wang X, Zhang X, Yang QX, Qing Z, et al. Olfactory dysfunction mediates adiposity in cognitive impairment of type 2 diabetes: insights from clinical and functional neuroimaging studies. Diabetes Care. 2019;42(7):1274–83.
pubmed: 31221697
doi: 10.2337/dc18-2584
Elias MF, Elias PK, Sullivan LM, Wolf PA, D’Agostino RB. Obesity, diabetes and cognitive deficit: the framingham heart study. Neurobiol Aging. 2005;26(Suppl 1):11–6.
pubmed: 16223549
doi: 10.1016/j.neurobiolaging.2005.08.019
Mina T, Yew YW, Ng HK, Sadhu N, Wansaicheong G, Dalan R, et al. Adiposity impacts cognitive function in Asian populations: an epidemiological and Mendelian Randomization study. Lancet Reg Health West Pac. 2023;33:100710.
pubmed: 36851942
pmcid: 9957736
Luchsinger JA, Patel B, Tang MX, Schupf N, Mayeux R. Measures of adiposity and dementia risk in elderly persons. Arch Neurol. 2007;64(3):392–8.
pubmed: 17353383
pmcid: 1821350
doi: 10.1001/archneur.64.3.392
Pedditzi E, Peters R, Beckett N. The risk of overweight/obesity in mid-life and late life for the development of dementia: a systematic review and meta-analysis of longitudinal studies. Age Ageing. 2016;45(1):14–21.
pubmed: 26764391
doi: 10.1093/ageing/afv151
Nkwana MR, Monyeki KD, Lebelo SL. Body Roundness index, a body shape index, conicity index, and their association with nutritional status and cardiovascular risk factors in South African Rural Young Adults. Int J Environ Res Public Health. 2021;18(1):281.
Dhana K, Koolhaas CM, Schoufour JD, Rivadeneira F, Hofman A, Kavousi M, et al. Association of anthropometric measures with fat and fat-free mass in the elderly: The Rotterdam study. Maturitas. 2016;88:96–100.
pubmed: 27105706
doi: 10.1016/j.maturitas.2016.03.018
Li J, Sun J, Zhang Y, Zhang B, Zhou L. Association between weight-adjusted-waist index and cognitive decline in US elderly participants. Front Nutr. 2024;11:1390282.
pubmed: 38903624
pmcid: 11187255
doi: 10.3389/fnut.2024.1390282
Huang SH, Chen SC, Geng JH, Wu DW, Li CH. Metabolic syndrome and high-obesity-related indices are associated with poor cognitive function in a large taiwanese population study older than 60 years. Nutrients. 2022;14(8):1535.
pubmed: 35458097
pmcid: 9026510
doi: 10.3390/nu14081535
Randrianarisoa E, Lehn-Stefan A, Hieronimus A, Rietig R, Fritsche A, Machann J, et al. Visceral Adiposity index as an independent marker of subclinical atherosclerosis in individuals prone to diabetes mellitus. J Atheroscler Thromb. 2019;26(9):821–34.
pubmed: 30787215
pmcid: 6753238
doi: 10.5551/jat.47274
Anand SS, Friedrich MG, Lee DS, Awadalla P, Despres JP, Desai D, et al. Evaluation of Adiposity and Cognitive Function in Adults. JAMA Netw Open. 2022;5(2):e2146324.
pubmed: 35103790
pmcid: 8808326
doi: 10.1001/jamanetworkopen.2021.46324
Zhao J, Cai X, Hu J, Song S, Zhu Q, Shen D, et al. J-Shaped Relationship Between Weight-Adjusted-Waist Index and Cardiovascular Disease Risk in Hypertensive Patients with Obstructive Sleep Apnea: A Cohort Study. Diabetes Metab Syndr Obes. 2024;17:2671–81.
pubmed: 38978818
pmcid: 11228610
doi: 10.2147/DMSO.S469376
Li Y, He Y, Yang L, Liu Q, Li C, Wang Y, et al. Body roundness index and waist-hip ratio result in better cardiovascular disease risk stratification: results from a large Chinese cross-sectional study. Front Nutr. 2022;9:801582.
pubmed: 35360688
pmcid: 8960742
doi: 10.3389/fnut.2022.801582
Cai X, Song S, Hu J, Zhu Q, Yang W, Hong J, et al. Body roundness index improves the predictive value of cardiovascular disease risk in hypertensive patients with obstructive sleep apnea: a cohort study. Clin Exp Hypertens. 2023;45(1):2259132.
pubmed: 37805984
doi: 10.1080/10641963.2023.2259132
Gardener H, Caunca M, Dong C, Cheung YK, Rundek T, Elkind MSV, et al. Obesity measures in relation to cognition in the Northern Manhattan study. J Alzheimers Dis. 2020;78(4):1653–60.
pubmed: 33164939
pmcid: 7902200
doi: 10.3233/JAD-201071
Shen J, Yu H, Li K, Ding B, Xiao R, Ma W. The association between plasma fatty acid and cognitive function mediated by inflammation in patients with type 2 diabetes mellitus. Diabetes Metab Syndr Obes. 2022;15:1423–36.
pubmed: 35573864
pmcid: 9091472
doi: 10.2147/DMSO.S353449
Taksali SE, Caprio S, Dziura J, Dufour S, Cali AM, Goodman TR, et al. High visceral and low abdominal subcutaneous fat stores in the obese adolescent: a determinant of an adverse metabolic phenotype. Diabetes. 2008;57(2):367–71.
pubmed: 17977954
doi: 10.2337/db07-0932
Pulit SL, Stoneman C, Morris AP, Wood AR, Glastonbury CA, Tyrrell J, et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet. 2019;28(1):166–74.
pubmed: 30239722
doi: 10.1093/hmg/ddy327
Ashwell M, Cole TJ, Dixon AK. Obesity: new insight into the anthropometric classification of fat distribution shown by computed tomography. Br Med J (Clin Res Ed). 1985;290(6483):1692–4.
pubmed: 3924217
doi: 10.1136/bmj.290.6483.1692
Seidell JC, Bjorntorp P, Sjostrom L, Sannerstedt R, Krotkiewski M, Kvist H. Regional distribution of muscle and fat mass in men–new insight into the risk of abdominal obesity using computed tomography. Int J Obes. 1989;13(3):289–303.
pubmed: 2767882
Heid IM, Jackson AU, Randall JC, Winkler TW, Qi L, Steinthorsdottir V, et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat Genet. 2010;42(11):949–60.
pubmed: 20935629
pmcid: 3000924
doi: 10.1038/ng.685
Chakraborty A, Hegde S, Praharaj SK, Prabhu K, Patole C, Shetty AK, et al. Age related prevalence of mild cognitive impairment in type 2 diabetes mellitus patients in the indian population and association of serum lipids with cognitive dysfunction. Front Endocrinol (Lausanne). 2021;12: 798652.
pubmed: 35035379
doi: 10.3389/fendo.2021.798652
Jia W, Weng J, Zhu D, Ji L, Lu J, Zhou Z, et al. Standards of medical care for type 2 diabetes in China 2019. Diabetes Metab Res Rev. 2019;35(6): e3158.
pubmed: 30908791
doi: 10.1002/dmrr.3158
Dale CE, Fatemifar G, Palmer TM, White J, Prieto-Merino D, Zabaneh D, et al. Causal associations of adiposity and body fat distribution with coronary heart disease, stroke subtypes, and type 2 diabetes mellitus: a mendelian randomization analysis. Circulation. 2017;135(24):2373–88.
pubmed: 28500271
pmcid: 5515354
doi: 10.1161/CIRCULATIONAHA.116.026560
Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9.
pubmed: 15817019
doi: 10.1111/j.1532-5415.2005.53221.x
Dong Y, Yean Lee W, Hilal S, Saini M, Wong TY, Chen CL, et al. Comparison of the Montreal Cognitive Assessment and the Mini-Mental State Examination in detecting multi-domain mild cognitive impairment in a Chinese sub-sample drawn from a population-based study. Int Psychogeriatr. 2013;25(11):1831–8.
pubmed: 23870281
doi: 10.1017/S1041610213001129
Xia X, Jiang Q, McDermott J, Han JJ. Aging and Alzheimer’s disease: comparison and associations from molecular to system level. Aging Cell. 2018;17(5):e12802.
pubmed: 29963744
pmcid: 6156542
doi: 10.1111/acel.12802
Jia L, Du Y, Chu L, Zhang Z, Li F, Lyu D, et al. Prevalence, risk factors, and management of dementia and mild cognitive impairment in adults aged 60 years or older in China: a cross-sectional study. Lancet Public Health. 2020;5(12):e661–71.
pubmed: 33271079
doi: 10.1016/S2468-2667(20)30185-7
Snyder HM, Asthana S, Bain L, Brinton R, Craft S, Dubal DB, et al. Sex biology contributions to vulnerability to Alzheimer’s disease: a think tank convened by the women’s Alzheimer’s research initiative. Alzheimers Dement. 2016;12(11):1186–96.
pubmed: 27692800
doi: 10.1016/j.jalz.2016.08.004
Rawlings AM, Sharrett AR, Albert MS, Coresh J, Windham BG, Power MC, et al. The association of late-life diabetes status and hyperglycemia with incident mild cognitive impairment and dementia: the ARIC study. Diabetes Care. 2019;42(7):1248–54.
pubmed: 31221696
pmcid: 6609963
doi: 10.2337/dc19-0120
Xing Z, Long C, Hu X, Chai X. Obesity is associated with greater cognitive function in patients with type 2 diabetes mellitus. Front Endocrinol (Lausanne). 2022;13:953826.
pubmed: 36353230
doi: 10.3389/fendo.2022.953826
Stewart R, Masaki K, Xue QL, Peila R, Petrovitch H, White LR, et al. A 32-year prospective study of change in body weight and incident dementia: the Honolulu-Asia Aging Study. Arch Neurol. 2005;62(1):55–60.
pubmed: 15642850
doi: 10.1001/archneur.62.1.55
Deng YT, Li YZ, Huang SY, Ou YN, Zhang W, Chen SD, et al. Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants. Mol Psychiatry. 2022;27(8):3385–95.
pubmed: 35538193
doi: 10.1038/s41380-022-01604-9
Ward MA, Carlsson CM, Trivedi MA, Sager MA, Johnson SC. The effect of body mass index on global brain volume in middle-aged adults: a cross sectional study. BMC Neurol. 2005;5: 23.
pubmed: 16321166
pmcid: 1325254
doi: 10.1186/1471-2377-5-23
Willeumier KC, Taylor DV, Amen DG. Elevated BMI is associated with decreased blood flow in the prefrontal cortex using SPECT imaging in healthy adults. Obesity (Silver Spring). 2011;19(5):1095–7.
pubmed: 21311507
doi: 10.1038/oby.2011.16
Wang X, Ji L, Tang Z, Ding G, Chen X, Lv J, et al. The association of metabolic syndrome and cognitive impairment in Jidong of China: a cross-sectional study. BMC Endocr Disord. 2021;21(1):40.
pubmed: 33663435
pmcid: 7934472
doi: 10.1186/s12902-021-00705-w
Cho GJ, Hwang SY, Lee KM, Choi KM, Hyun Baik S, Kim T, et al. Association between waist circumference and dementia in older persons: a nationwide population-based study. Obesity (Silver Spring). 2019;27(11):1883–91.
pubmed: 31689005
doi: 10.1002/oby.22609
Moh MC, Low S, Ng TP, Wang J, Ang SF, Tan C, et al. Association of traditional and novel measures of central obesity with cognitive performance in older multi-ethnic Asians with type 2 diabetes. Clin Obes. 2020;10(2):e12352.
pubmed: 32020768
doi: 10.1111/cob.12352
Ren Z, Li Y, Li X, Shi H, Zhao H, He M, et al. Associations of body mass index, waist circumference and waist-to-height ratio with cognitive impairment among Chinese older adults: based on the CLHLS. J Affect Disord. 2021;295:463–70.
pubmed: 34507227
doi: 10.1016/j.jad.2021.08.093
Abbatecola AM, Lattanzio F, Spazzafumo L, Molinari AM, Cioffi M, Canonico R, et al. Adiposity predicts cognitive decline in older persons with diabetes: a 2-year follow-up. PLoS ONE. 2010;5(4): e10333.
pubmed: 20428239
pmcid: 2859057
doi: 10.1371/journal.pone.0010333
Tang X, Zhao W, Lu M, Zhang X, Zhang P, Xin Z, et al. Relationship between Central Obesity and the incidence of Cognitive Impairment and Dementia from Cohort Studies Involving 5,060,687 Participants. Neurosci Biobehav Rev. 2021;130:301–13.
pubmed: 34464646
doi: 10.1016/j.neubiorev.2021.08.028
Zuin M, Roncon L, Passaro A, Cervellati C, Zuliani G. Metabolic syndrome and the risk of late onset Alzheimer’s disease: an updated review and meta-analysis. Nutr Metab Cardiovasc Dis. 2021;31(8):2244–52.
pubmed: 34039508
doi: 10.1016/j.numecd.2021.03.020
Uchida K, Sugimoto T, Tange C, Nishita Y, Shimokata H, Saji N, et al. Association between abdominal adiposity and cognitive decline in older adults: a 10-year community-based study. J Nutr Health Aging. 2024;28(3): 100175.
pubmed: 38308924
doi: 10.1016/j.jnha.2024.100175
Xu Z, Liu Y, Yan C, Yang R, Xu L, Guo Z, et al. Measurement of visceral fat and abdominal obesity by single-frequency bioelectrical impedance and CT: a cross-sectional study. BMJ Open. 2021;11(10): e048221.
pubmed: 34635516
pmcid: 8506854
doi: 10.1136/bmjopen-2020-048221
Wang SH, Su MH, Chen CY, Lin YF, Feng YA, Hsiao PC, et al. Causality of abdominal obesity on cognition: a trans-ethnic Mendelian randomization study. Int J Obes (Lond). 2022;46(8):1487–92.
pubmed: 35538205
doi: 10.1038/s41366-022-01138-8
Chen W, Feng J, Guo J, Dong S, Li R, Ngo JCK, et al. Obesity causally influencing brain cortical structure: a Mendelian randomization study. Cereb Cortex. 2023;33(15):9409–16.
pubmed: 37328935
doi: 10.1093/cercor/bhad214
Morys F, Dadar M, Dagher A. Association between midlife obesity and its metabolic consequences, cerebrovascular disease, and cognitive decline. J Clin Endocrinol Metab. 2021;106(10):e4260–74.
pubmed: 33677592
pmcid: 8475210
doi: 10.1210/clinem/dgab135
Powell-Wiley TM, Poirier P, Burke LE, Despres JP, Gordon-Larsen P, Lavie CJ, et al. Obesity and cardiovascular disease: a scientific statement from the American heart association. Circulation. 2021;143(21):e984–1010.
pubmed: 33882682
pmcid: 8493650
doi: 10.1161/CIR.0000000000000973
Livingston G, Sommerlad A, Orgeta V, Costafreda SG, Huntley J, Ames D, et al. Dementia prevention, intervention, and care. Lancet. 2017;390(10113):2673–734.
pubmed: 28735855
doi: 10.1016/S0140-6736(17)31363-6
Lipnicki DM, Crawford J, Kochan NA, Trollor JN, Draper B, Reppermund S, et al. Risk factors for mild cognitive impairment, dementia and mortality: the Sydney memory and ageing study. J Am Med Dir Assoc. 2017;18(5):388–95.
pubmed: 28043804
doi: 10.1016/j.jamda.2016.10.014
Letra L, Santana I, Seica R. Obesity as a risk factor for Alzheimer’s disease: the role of adipocytokines. Metab Brain Dis. 2014;29(3):563–8.
pubmed: 24553879
doi: 10.1007/s11011-014-9501-z
Park HS, Park JY, Yu R. Relationship of obesity and visceral adiposity with serum concentrations of CRP, TNF-alpha and IL-6. Diabetes Res Clin Pract. 2005;69(1):29–35.
pubmed: 15955385
doi: 10.1016/j.diabres.2004.11.007
Yaghootkar H, Lotta LA, Tyrrell J, Smit RA, Jones SE, Donnelly L, et al. Genetic evidence for a link between favorable adiposity and lower risk of type 2 diabetes, hypertension, and heart disease. Diabetes. 2016;65(8):2448–60.
pubmed: 27207519
doi: 10.2337/db15-1671
Irving A, Harvey J. Regulation of hippocampal synaptic function by the metabolic hormone leptin: Implications for health and disease. Prog Lipid Res. 2021;82:101098.
pubmed: 33895229
doi: 10.1016/j.plipres.2021.101098
Ma W, Zhang H, Wu N, Liu Y, Han P, Wang F, et al. Relationship between obesity-related anthropometric indicators and cognitive function in Chinese suburb-dwelling older adults. PLoS ONE. 2021;16(10): e0258922.
pubmed: 34705855
pmcid: 8550380
doi: 10.1371/journal.pone.0258922
Zhou Y, Sun X, Zhou M. Body Shape and Alzheimer’s Disease: a Mendelian randomization analysis. Front Neurosci. 2019;13:1084.
pubmed: 31649504
pmcid: 6795688
doi: 10.3389/fnins.2019.01084
Trzepacz PT, Hochstetler H, Wang S, Walker B, Saykin AJ. Relationship between the montreal cognitive assessment and mini-mental State Examination for assessment of mild cognitive impairment in older adults. BMC Geriatr. 2015;15:107.
pubmed: 26346644
pmcid: 4562190
doi: 10.1186/s12877-015-0103-3